From bc150f5a4d77e67f4612d7b3e194db2f8ca300c2 Mon Sep 17 00:00:00 2001
From: Dominik Roth <dominik.roth.dev@gmail.com>
Date: Wed, 11 Oct 2023 11:59:02 +0200
Subject: [PATCH] Fix: Bibtex in README mixed between tabs & spaces
---
README.md | 17 ++++++++---------
1 file changed, 8 insertions(+), 9 deletions(-)
diff --git a/README.md b/README.md
index eb702c1..8b82975 100644
--- a/README.md
+++ b/README.md
@@ -186,14 +186,13 @@ class RawInterfaceWrapper(gym.Wrapper):
@property
def context_mask(self) -> np.ndarray:
"""
- Returns boolean mask of the same shape as the observation space.
- It determines whether the observation is returned for the contextual case or not.
- This effectively allows to filter unwanted or unnecessary observations from the full step-based case.
- E.g. Velocities starting at 0 are only changing after the first action. Given we only receive the
- context/part of the first observation, the velocities are not necessary in the observation for the task.
- Returns:
- bool array representing the indices of the observations
-
+ Returns boolean mask of the same shape as the observation space.
+ It determines whether the observation is returned for the contextual case or not.
+ This effectively allows to filter unwanted or unnecessary observations from the full step-based case.
+ E.g. Velocities starting at 0 are only changing after the first action. Given we only receive the
+ context/part of the first observation, the velocities are not necessary in the observation for the task.
+ Returns:
+ bool array representing the indices of the observations
"""
return np.ones(self.env.observation_space.shape[0], dtype=bool)
@@ -276,7 +275,7 @@ To cite this repository in publications:
author = {Otto, Fabian and Celik, Onur and Roth, Dominik and Zhou, Hongyi},
abstract = {Fancy Gym: Unifying interface for various RL benchmarks with support for Black Box approaches.},
url = {https://github.com/ALRhub/fancy_gym},
- organization = {Autonomous Learning Robots Lab (ALR) @ KIT},
+ organization = {Autonomous Learning Robots Lab (ALR) @ KIT},
}
```